Reconstructing SMAP-derived 1-km Soil Moisture Dataset Using DINEOF+ Algorithm-Reference-Cited by-同舟云学术

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Reconstructing SMAP-derived 1-km Soil Moisture Dataset Using DINEOF+ Algorithm

Published:2024-07-15 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 12th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)
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Author:

Zhao Haoteng¹,Zhao Haipeng²,Zhang Chen³

Affiliation:

1. Hydrology and Remote Sensing Lab USDA-ARS & ORISE,Beltsville,MD,USA

2. Duke University Durham,Division of Earth and Climate Sciences, Nicholas School of the Environment,NC,USA

3. George Mason University Fairfax,Center for Spatial Information Science and Systems,VA,USA

Funder

Agricultural Research Service

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10660664/10660668/10661101.pdf?arnumber=10661101

Reference12 articles.

1. Impacts of Soil Moisture on Crop Health: A Remote Sensing Perspective

2. Validation and Calibration of HRLDAS Soil Moisture Products in Nebraska

3. More Extreme Precipitation in Chinese Deserts From 1960 to 2018

4. Heterogeneous sea-level rises along coastal zones and small islands

5. A global 1‐km downscaled SMAP soil moisture product based on thermal inertia theory

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